"""simple docstring"""


import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


a				=get_tests_dir('fixtures/test_sentencepiece.model')






@require_sentencepiece
@require_tokenizers
class   __UpperCAmelCase		(      __lowerCAmelCase , unittest.TestCase      ):
				A__ :  Optional[Any]    				=			ReformerTokenizer
				A__ :  Tuple    				=			ReformerTokenizerFast
				A__ :  Tuple    				=			True
				A__ :  Any    				=			False
				A__ :  Tuple    				=			True

				def 						_a      ( self ):
										super().setUp()

										lowerCamelCase__   =ReformerTokenizer(_lowerCamelCase      ,					keep_accents=_lowerCamelCase )
										tokenizer.save_pretrained(self.tmpdirname )

				def 						_a      ( self ):
										lowerCamelCase__   ="<s>"
										lowerCamelCase__   =1

										self.assertEqual(self.get_tokenizer()._convert_token_to_id(_lowerCamelCase )      ,					_lowerCamelCase )
										self.assertEqual(self.get_tokenizer()._convert_id_to_token(_lowerCamelCase )      ,					_lowerCamelCase )

				def 						_a      ( self ):
										lowerCamelCase__   =list(self.get_tokenizer().get_vocab().keys() )

										self.assertEqual(vocab_keys[0]      ,					"<unk>" )
										self.assertEqual(vocab_keys[1]      ,					"<s>" )
										self.assertEqual(vocab_keys[-1]      ,					"j" )
										self.assertEqual(len(_lowerCamelCase )      ,					1000 )

				def 						_a      ( self ):
										self.assertEqual(self.get_tokenizer().vocab_size      ,					1000 )

				def 						_a      ( self ):
										if not self.test_rust_tokenizer:
																return

										lowerCamelCase__   =self.get_tokenizer()
										lowerCamelCase__   =self.get_rust_tokenizer()

										lowerCamelCase__   ="I was born in 92000, and this is falsé."

										lowerCamelCase__   =tokenizer.tokenize(_lowerCamelCase )
										lowerCamelCase__   =rust_tokenizer.tokenize(_lowerCamelCase )
										self.assertListEqual(_lowerCamelCase      ,					_lowerCamelCase )

										lowerCamelCase__   =tokenizer.encode(_lowerCamelCase      ,					add_special_tokens=_lowerCamelCase )
										lowerCamelCase__   =rust_tokenizer.encode(_lowerCamelCase      ,					add_special_tokens=_lowerCamelCase )
										self.assertListEqual(_lowerCamelCase      ,					_lowerCamelCase )

										lowerCamelCase__   =self.get_rust_tokenizer()
										lowerCamelCase__   =tokenizer.encode(_lowerCamelCase )
										lowerCamelCase__   =rust_tokenizer.encode(_lowerCamelCase )
										self.assertListEqual(_lowerCamelCase      ,					_lowerCamelCase )

				def 						_a      ( self      ,					_lowerCamelCase=15 ):
										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})''' ):
																						lowerCamelCase__   =self.rust_tokenizer_class.from_pretrained(_lowerCamelCase      ,					**_lowerCamelCase )

																						# Simple input
																						lowerCamelCase__   ="This is a simple input"
																						lowerCamelCase__   =["This is a simple input 1", "This is a simple input 2"]
																						lowerCamelCase__   =("This is a simple input", "This is a pair")
																						lowerCamelCase__   =[
																						    ("This is a simple input 1", "This is a simple input 2"),
																						    ("This is a simple pair 1", "This is a simple pair 2"),
																						]

																						# Simple input tests
																						self.assertRaises(_lowerCamelCase      ,					tokenizer_r.encode      ,					_lowerCamelCase      ,					max_length=_lowerCamelCase      ,					padding="max_length" )

																						# Simple input
																						self.assertRaises(_lowerCamelCase      ,					tokenizer_r.encode_plus      ,					_lowerCamelCase      ,					max_length=_lowerCamelCase      ,					padding="max_length" )

																						# Simple input
																						self.assertRaises(
																						    _lowerCamelCase      ,					tokenizer_r.batch_encode_plus      ,					_lowerCamelCase      ,					max_length=_lowerCamelCase      ,					padding="max_length"      ,					)

																						# Pair input
																						self.assertRaises(_lowerCamelCase      ,					tokenizer_r.encode      ,					_lowerCamelCase      ,					max_length=_lowerCamelCase      ,					padding="max_length" )

																						# Pair input
																						self.assertRaises(_lowerCamelCase      ,					tokenizer_r.encode_plus      ,					_lowerCamelCase      ,					max_length=_lowerCamelCase      ,					padding="max_length" )

																						# Pair input
																						self.assertRaises(
																						    _lowerCamelCase      ,					tokenizer_r.batch_encode_plus      ,					_lowerCamelCase      ,					max_length=_lowerCamelCase      ,					padding="max_length"      ,					)

				def 						_a      ( self ):
										pass

				def 						_a      ( self ):
										lowerCamelCase__   =ReformerTokenizer(_lowerCamelCase      ,					keep_accents=_lowerCamelCase )

										lowerCamelCase__   =tokenizer.tokenize("This is a test" )
										self.assertListEqual(_lowerCamelCase      ,					["▁This", "▁is", "▁a", "▁t", "est"] )

										self.assertListEqual(
										    tokenizer.convert_tokens_to_ids(_lowerCamelCase )      ,					[285, 46, 10, 170, 382]      ,					)

										lowerCamelCase__   =tokenizer.tokenize("I was born in 92000, and this is falsé." )
										self.assertListEqual(
										    _lowerCamelCase      ,					[
										        SPIECE_UNDERLINE + "I",
										        SPIECE_UNDERLINE + "was",
										        SPIECE_UNDERLINE + "b",
										        "or",
										        "n",
										        SPIECE_UNDERLINE + "in",
										        SPIECE_UNDERLINE + "",
										        "9",
										        "2",
										        "0",
										        "0",
										        "0",
										        ",",
										        SPIECE_UNDERLINE + "and",
										        SPIECE_UNDERLINE + "this",
										        SPIECE_UNDERLINE + "is",
										        SPIECE_UNDERLINE + "f",
										        "al",
										        "s",
										        "é",
										        ".",
										    ]      ,					)
										lowerCamelCase__   =tokenizer.convert_tokens_to_ids(_lowerCamelCase )
										self.assertListEqual(
										    _lowerCamelCase      ,					[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]      ,					)

										lowerCamelCase__   =tokenizer.convert_ids_to_tokens(_lowerCamelCase )
										self.assertListEqual(
										    _lowerCamelCase      ,					[
										        SPIECE_UNDERLINE + "I",
										        SPIECE_UNDERLINE + "was",
										        SPIECE_UNDERLINE + "b",
										        "or",
										        "n",
										        SPIECE_UNDERLINE + "in",
										        SPIECE_UNDERLINE + "",
										        "<unk>",
										        "2",
										        "0",
										        "0",
										        "0",
										        ",",
										        SPIECE_UNDERLINE + "and",
										        SPIECE_UNDERLINE + "this",
										        SPIECE_UNDERLINE + "is",
										        SPIECE_UNDERLINE + "f",
										        "al",
										        "s",
										        "<unk>",
										        ".",
										    ]      ,					)

				@cached_property
				def 						_a      ( self ):
										return ReformerTokenizer.from_pretrained("google/reformer-crime-and-punishment" )

				@slow
				def 						_a      ( self ):
										lowerCamelCase__   ="Hello World!"
										lowerCamelCase__   =[126, 32, 262, 152, 38, 72, 287]

										self.assertListEqual(_lowerCamelCase      ,					self.big_tokenizer.encode(_lowerCamelCase ) )

				@slow
				def 						_a      ( self ):
										lowerCamelCase__   =(
										    "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
										    " add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"
										)
										lowerCamelCase__   =[
										    108,
										    265,
										    24,
										    111,
										    4,
										    258,
										    156,
										    35,
										    28,
										    275,
										    3,
										    259,
										    297,
										    260,
										    84,
										    4,
										    35,
										    110,
										    44,
										    8,
										    259,
										    91,
										    268,
										    21,
										    11,
										    209,
										    274,
										    109,
										    266,
										    277,
										    117,
										    86,
										    93,
										    315,
										    258,
										    278,
										    258,
										    277,
										    258,
										    0,
										    258,
										    288,
										    258,
										    319,
										    258,
										    0,
										    258,
										    0,
										    258,
										    0,
										    258,
										    0,
										    258,
										    287,
										    258,
										    315,
										    258,
										    289,
										    258,
										    278,
										    99,
										    269,
										    266,
										    262,
										    8,
										    259,
										    241,
										    4,
										    217,
										    230,
										    268,
										    266,
										    55,
										    168,
										    106,
										    75,
										    193,
										    266,
										    223,
										    27,
										    49,
										    26,
										    282,
										    25,
										    264,
										    299,
										    19,
										    26,
										    0,
										    258,
										    277,
										    117,
										    86,
										    93,
										    176,
										    183,
										    270,
										    11,
										    262,
										    42,
										    61,
										    265,
										]

										self.assertListEqual(_lowerCamelCase      ,					self.big_tokenizer.encode(_lowerCamelCase ) )

				@require_torch
				@slow
				def 						_a      ( self ):
										import torch

										from transformers import ReformerConfig, ReformerModel

										# Build sequence
										lowerCamelCase__   =list(self.big_tokenizer.get_vocab().keys() )[:10]
										lowerCamelCase__   =" ".join(_lowerCamelCase )
										lowerCamelCase__   =self.big_tokenizer.encode_plus(_lowerCamelCase      ,					return_tensors="pt" )
										lowerCamelCase__   =self.big_tokenizer.batch_encode_plus([sequence, sequence]      ,					return_tensors="pt" )

										lowerCamelCase__   =ReformerConfig()
										# The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
										lowerCamelCase__   =encoded_sequence["input_ids"].shape
										lowerCamelCase__   =ReformerModel(_lowerCamelCase )

										# Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
										assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

										with torch.no_grad():
																model(**_lowerCamelCase )
																model(**_lowerCamelCase )






				@slow
				def 						_a      ( self ):
										# fmt: off
										lowerCamelCase__   ={"input_ids": [[108, 265, 24, 111, 4, 258, 156, 7, 51, 279, 58, 7, 76, 25, 69, 278], [140, 243, 264, 134, 17, 267, 77, 263, 22, 262, 297, 258, 304, 177, 279, 266, 14, 89, 13, 35, 261, 299, 272, 137, 275, 278]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
										# fmt: on

										# This tokenizer does not know some characters like ")".
										# That is the reason why we use very simple texts here.
										# Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
										lowerCamelCase__   =[
										    "This is a very simple sentence.",
										    "The quick brown fox jumps over the lazy dog.",
										]

										self.tokenizer_integration_test_util(
										    expected_encoding=_lowerCamelCase      ,					model_name="google/reformer-crime-and-punishment"      ,					revision="0e6c3decb8211d49bf881013425dc8b0448b3f5a"      ,					padding=_lowerCamelCase      ,					sequences=_lowerCamelCase      ,					)



"""simple docstring"""


def      lowerCamelCase_					(   __lowerCAmelCase  ,       __lowerCAmelCase  ,       __lowerCAmelCase							)				->   int:




						'''simple docstring'''



						def update_area_of_max_square(__lowerCAmelCase  ,       __lowerCAmelCase							) -> int:
												# BASE CASE
												if row >= rows or col >= cols:
																		return 0

												lowerCamelCase__   =update_area_of_max_square(__lowerCAmelCase  ,       col + 1							)
												lowerCamelCase__   =update_area_of_max_square(row + 1  ,       col + 1							)
												lowerCamelCase__   =update_area_of_max_square(row + 1  ,       __lowerCAmelCase							)

												if mat[row][col]:
																		lowerCamelCase__   =1 + min([right, diagonal, down]							)
																		lowerCamelCase__   =max(largest_square_area[0]  ,       __lowerCAmelCase							)
																		return sub_problem_sol
												else:
																		return 0

						lowerCamelCase__   =[0]
						update_area_of_max_square(0  ,       0							)
						return largest_square_area[0]





def      lowerCamelCase_					(   __lowerCAmelCase  ,       __lowerCAmelCase  ,       __lowerCAmelCase							)				->   int:




						'''simple docstring'''



						def update_area_of_max_square_using_dp_array(
						    __lowerCAmelCase  ,       __lowerCAmelCase  ,       __lowerCAmelCase							) -> int:
												if row >= rows or col >= cols:
																		return 0
												if dp_array[row][col] != -1:
																		return dp_array[row][col]

												lowerCamelCase__   =update_area_of_max_square_using_dp_array(__lowerCAmelCase  ,       col + 1  ,       __lowerCAmelCase							)
												lowerCamelCase__   =update_area_of_max_square_using_dp_array(row + 1  ,       col + 1  ,       __lowerCAmelCase							)
												lowerCamelCase__   =update_area_of_max_square_using_dp_array(row + 1  ,       __lowerCAmelCase  ,       __lowerCAmelCase							)

												if mat[row][col]:
																		lowerCamelCase__   =1 + min([right, diagonal, down]							)
																		lowerCamelCase__   =max(largest_square_area[0]  ,       __lowerCAmelCase							)
																		lowerCamelCase__   =sub_problem_sol
																		return sub_problem_sol
												else:
																		return 0

						lowerCamelCase__   =[0]
						lowerCamelCase__   =[[-1] * cols for _ in range(__lowerCAmelCase							)]
						update_area_of_max_square_using_dp_array(0  ,       0  ,       __lowerCAmelCase							)

						return largest_square_area[0]





def      lowerCamelCase_					(   __lowerCAmelCase  ,       __lowerCAmelCase  ,       __lowerCAmelCase							)				->   int:




						'''simple docstring'''



						lowerCamelCase__   =[[0] * (cols + 1) for _ in range(rows + 1							)]
						lowerCamelCase__   =0
						for row in range(rows - 1  ,       -1  ,       -1							):
												for col in range(cols - 1  ,       -1  ,       -1							):
																		lowerCamelCase__   =dp_array[row][col + 1]
																		lowerCamelCase__   =dp_array[row + 1][col + 1]
																		lowerCamelCase__   =dp_array[row + 1][col]

																		if mat[row][col] == 1:
																								lowerCamelCase__   =1 + min(__lowerCAmelCase  ,       __lowerCAmelCase  ,       __lowerCAmelCase							)
																								lowerCamelCase__   =max(dp_array[row][col]  ,       __lowerCAmelCase							)
																		else:
																								lowerCamelCase__   =0

						return largest_square_area





def      lowerCamelCase_					(   __lowerCAmelCase  ,       __lowerCAmelCase  ,       __lowerCAmelCase							)				->   int:




						'''simple docstring'''



						lowerCamelCase__   =[0] * (cols + 1)
						lowerCamelCase__   =[0] * (cols + 1)
						lowerCamelCase__   =0
						for row in range(rows - 1  ,       -1  ,       -1							):
												for col in range(cols - 1  ,       -1  ,       -1							):
																		lowerCamelCase__   =current_row[col + 1]
																		lowerCamelCase__   =next_row[col + 1]
																		lowerCamelCase__   =next_row[col]

																		if mat[row][col] == 1:
																								lowerCamelCase__   =1 + min(__lowerCAmelCase  ,       __lowerCAmelCase  ,       __lowerCAmelCase							)
																								lowerCamelCase__   =max(current_row[col]  ,       __lowerCAmelCase							)
																		else:
																								lowerCamelCase__   =0
												lowerCamelCase__   =current_row

						return largest_square_area


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	print(largest_square_area_in_matrix_bottom_up(2, 2, [[1, 1], [1, 1]]))


